Computed Tomography (CT) is one of the most important means for medical diagnosis currently. According to the difference in absorption and transmittance rate of X-ray of different human tissues, a highly sensitive instrument is used to measure a human body and then the data acquired from the measurement is input to a electronic computer, which then processes the data and obtains a cross-sectional or three-dimensional image of the part of human body under detection (i.e. CT imaging technology), so as to find any tiny lesion in any part within the body.
However, in the process of CT imaging, a metal object on the patient body, such as a false tooth or surgically implanted metal object will cause a change in the hardness of the X-ray beam, which results in a metal artifact. Since occurrence of a metal artifact influences the recognition of pathologic analysis after the CT imaging, the determination on lesion is thus inaccurate. Therefore, there have been medical image processing methods for the purpose of metal artifact elimination. However, after artifact elimination processing through the methods in the prior art, a new artifact is usually introduced into the image and the boundary of a metal region will be blurred.
The methods for artifact elimination in the prior art perform an overall processing to a medical image where a metal object is contained according to the presence of the metal object is detected, so that a region where no artifact is contained in the medical image or a region where the artifact is insufficient to affect the definition of the medical image also undergoes the same artifact elimination processing as an artifact region that actually needs to be processed. This results in over-intensification of the image for an artifact region that does not necessary to be processed, whereby a new artifact is generated. In the meanwhile, it may also result in blurring of a boundary of a metal region thereof. There is a solution for boundary blurring in the prior art, that is, processing all metal object regions without considering an artifact portion in the surrounding or other positions, as a result, the brightness of the display of the metal object portion is increased to cover the metal artifact. The result of such processing is that the boundary of a metal region is still not clear enough and the whole CT image is still excessively modified. Therefore, the methods in the prior art still fail to achieve proper artifact elimination, instead, a new artifact is generated and the boundary of metal is still not clear enough. Furthermore, the methods in the prior art fails to enhance the effect of distinguishable lesion in an original medical image, besides, application cost increases.
Thus, it is necessary to provide a new method and apparatus for metal artifact elimination in a medical image to enhance the imaging quality.